Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/rand/mnemosyne/feature-specifygit clone --depth 1 https://github.com/rand/mnemosyneWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00012 | $0.01998 |
| Opus 5 | $0.00006 | $0.00999 |
| Sonnet 5 | $0.00002 | $0.00400 |
| Haiku 4.5 | $0.00001 | $0.00200 |
Grade A, and why
feature-specify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
I will help you create a feature specification following the specification workflow. This will capture user scenarios, requirements, and acceptance criteria in a structured format.
Usage:
/feature-specify <brief description>- Create new feature spec/feature-specify --from-branch- Create spec from current git branch/feature-specify --show <feature-id>- Display existing spec
Instructions for me:
-
Generate feature ID:
- If
--from-branch: Use current git branch namegit branch --show-current - Otherwise: Convert description to kebab-case (e.g., "JWT Authentication" → "jwt-authentication")
- Max 50 characters
- Format:
{category}-{name}(e.g.,auth-jwt,ui-dashboard,api-rate-limiting)
- If
-
Check for existing spec:
- Look for
.mnemosyne/artifacts/specs/<feature-id>.md - If exists: Ask if user wants to update (increment version) or view
- If updating: Parse current version and increment
- Look for
-
Gather feature details (if creating new): Ask the user about:
a) Feature Overview:
- Feature name (human-readable)
- Brief description (1-2 sentences)
- Why this feature? (business value)
b) User Scenarios (prioritized): For each scenario (start with P0/P1):
- Priority: P0 (critical), P1 (high), P2 (medium), P3 (nice-to-have)
- Actor: "As a [user type]..."
- Goal: "I want [capability]..."
- Benefit: "So that [value]..."
- Acceptance Criteria: 3-7 specific, testable criteria
c) Requirements:
- Functional requirements
- Non-functional requirements (performance, security, etc.)
- Constraints or limitations
d) Success Criteria:
- How will we know this is successful?
- What metrics matter?
-
Check constitution alignment:
- Load
.mnemosyne/artifacts/constitution/project-constitution.md - Verify feature aligns with core principles
- Flag any conflicts (e.g., performance requirement vs. constitution)
- If misaligned: Ask user to clarify or adjust
- Load
-
Format spec as markdown:
--- type: feature_spec id: <feature-id> name: <feature-name> branch: <branch-name> version: 1.0.0 status: draft created_at: <ISO 8601 timestamp> updated_at: <ISO 8601 timestamp> memory_id: <will be filled after storage> references: [<constitution-memory-id>] --- # Feature: <feature-name> ## Overview <brief description> **Business Value**: <why this matters> ## User Scenarios (Prioritized) ### P0: <Scenario Name> **As a** <actor> **I want** <goal> **So that** <benefit> **Acceptance Criteria**: - [ ] <criterion 1> - [ ] <criterion 2> - [ ] <criterion 3> ### P1: <Scenario Name> ... ## Requirements ### Functional - <requirement> ### Non-Functional - **Performance**: <requirement> - **Security**: <requirement> - **Scalability**: <requirement> ### Constraints - <constraint> ## Success Criteria - <criterion> ## Open Questions - [ ] <question needing clarification> ## Related - Constitution: `.mnemosyne/artifacts/constitution/project-constitution.md` - Parent Feature: <if sub-feature> -
Write spec file:
- Create
.mnemosyne/artifacts/specs/<feature-id>.md - Ensure
.mnemosyne/artifacts/specs/directory exists
- Create
-
Store memory entry:
- Use Mnemosyne CLI:
mnemosyne remember - Arguments:
- Content: Feature overview + first P0 scenario + "...see .mnemosyne/artifacts/specs/.md for full spec"
- Namespace:
project:<project-name>(detect from git) - Importance: 8 (specs are important)
- Type: feature_spec
- Tags: spec,feature,
- Context: "Feature specification for "
- Capture memory_id from output
- Use Mnemosyne CLI:
-
Create memory link to constitution:
- Get constitution memory_id from
.mnemosyne/artifacts/constitution/project-constitution.mdfrontmatter - Link spec → constitution with relationship "builds_upon"
- Update spec's
referencesfield in frontmatter
- Get constitution memory_id from
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 245 lines · 12 tokens per session scan A d9e71aac9003
feature-specify is a command published in the GitHub repository rand/mnemosyne (84 stars, last pushed 9mo ago), licensed MIT. It adds 12 tokens to every session and 1,998 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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